18,639 Data Scientists jobs in India

Were Hiring: Data Scientists Enterprise AI, ML & Advanced Analytics

(30+ Openings | 3-20 Yrs Exp | Multiple Levels)

Location: Mumbai / Pune / Chandigarh / Bengaluru / Gurugram / Noida / New Delhi / Kolkata / Hyderabad / Chennai (Remote and Hybrid options are available for some roles)

Industry: Fortune 500 Client Projects (Staffing via Hatchtra Innotech Pvt Ltd)

Employment Type: Full-Time | Contract (C2H)

About us:

Hatchtra is a leading staffing and workforce solutions company, trusted by Fortune 500 organizations and global enterprises to build their technology teams.

When you join us, you'll work directly with our Fortune 500 client teams that power mission-critical systems worldwide.

About the Role

We are seeking Data Scientists (3-20 years) to deliver advanced analytics, AI, and machine learning solutions for global enterprises. This role is perfect for professionals who thrive on solving complex business problems, building predictive models, and driving data-driven innovation at scale.

As part of world-class analytics teams, youll work on enterprise AI initiatives, ML model deployment, NLP, computer vision, and generative AI use cases to transform business outcomes.

Open Positions & Designations

• Associate Data Scientist / Junior ML Engineer (3–5 Yrs)
• Data Scientist / Senior Data Scientist (5–10 Yrs)
• Lead Data Scientist / AI Engineer (8–12 Yrs)
• Principal Data Scientist / AI Solutions Architect (10–15 Yrs)
• Director – Data Science & AI Strategy (15–20 Yrs)

Key Responsibilities (Scale with Level)

Professional (3–5 Yrs)

• Clean, preprocess, and analyze structured and unstructured data for model building.
• Build and evaluate ML models (classification, regression, clustering).
• Work with Python, R, and libraries like Scikit-learn, TensorFlow, PyTorch.
• Support data preparation, feature engineering, and exploratory data analysis (EDA).
• Create basic dashboards and visualizations to share findings with stakeholders.
• Collaborate with data engineers to productionize analytics pipelines.

Mid-Level (5–10 Yrs)

• Design and deploy end-to-end ML/AI solutions in enterprise environments.
• Develop deep learning models for NLP, computer vision, and recommendation systems.
• Integrate ML pipelines with cloud data platforms (AWS SageMaker, Azure ML, GCP Vertex AI).
• Implement MLOps best practices for model lifecycle management.
• Conduct advanced statistical modeling, A/B testing, and causal inference.
• Mentor junior team members and lead analytics initiatives.

Senior/Leadership (10–20 Yrs)

• Define and execute enterprise AI and data science strategy.
• Lead AI innovation programs (Generative AI, LLMs, reinforcement learning).
• Partner with executives to drive AI-driven digital transformation initiatives.
• Build and manage global data science teams and delivery frameworks.
• Ensure AI/ML governance, ethical AI compliance, and data privacy standards.
• Represent organization in AI/ML conferences, publications, and thought leadership.

Skills & Tools

• Core Skills: Machine Learning, Deep Learning, NLP, Predictive Modeling, AI Solutions
• Programming: Python, R, SQL, Java, Scala
• ML Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, Hugging Face Transformers
• Cloud AI Platforms: AWS SageMaker, Azure ML, GCP Vertex AI
• Big Data: Spark, Databricks, Snowflake, BigQuery, Redshift
• Visualization: Power BI, Tableau, Matplotlib, Seaborn
• MLOps Tools: MLflow, Kubeflow, Airflow, Docker, Kubernetes

• Preferred Certifications:

• Google Professional Machine Learning Engineer

• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

Qualifications

• Bachelor's/Master's/PhD in Data Science, Computer Science, Statistics, Mathematics, or related field.
• 3+ years of experience in data science, AI, or advanced analytics roles.
• Proven expertise in building ML/DL models and deploying them in production.
• Experience with big data ecosystems and cloud AI platforms.
• For leadership roles: Strong experience in strategy, innovation, and global team management.

Why Join Us?

• Collaborate with Fortune 500 enterprises on AI-first transformation projects.
• Work on cutting-edge ML, deep learning, NLP, and generative AI initiatives.
• Exposure to global projects, certifications, and leadership opportunities.
• Competitive compensation, remote flexibility, and global career growth.

How to Apply

For quick consideration, please email your resume and include the desired position and experience level (e.g., "Data Engineer – Mid-Level") in the subject line.

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

• Frontend Framework: Angular

• Servers : Tomcat, Jetty, JBoss, Nginx, Apache HTTP Server

• Tools : Maven, Log4j 2, JUnit 5, Mockito, Postman, Swagger,

JMeter, Logback

• OS : Windows, Linux

• Version Control : Git, GitHub

• IDE : Eclipse, STS, IntelliJ IDEA

• Messaging Systems : Apache Kafka

• Cloud : AWS, Azure

• DevOps Tools : Docker, Kubernetes, GitLab

• Frontend Framework: Angular

• Servers : Tomcat, Jetty, JBoss, Nginx, Apache HTTP Server

• Tools : Maven, Log4j 2, JUnit 5, Mockito, Postman, Swagger,

JMeter, Logback

• OS : Windows, Linux

• Version Control : Git, GitHub

• IDE : Eclipse, STS, IntelliJ IDEA

• Messaging Systems : Apache Kafka

• Cloud : AWS, Azure

• DevOps Tools : Docker, Kubernetes, GitLab

Data scientists, BULK HIRE - TOP RATED MNC Completely Remote

PERMANENT HIRE

100% MNC CLIENT

100% WFH

MUST: 6 to 10 years YEARS EXPERIENCE AS data scientist

MAX 28L LPA

IMMEDIATE JOINERS ONLY

.IN /

Required Candidate profile

MUST: 6+ yrs as data scientist

Strong exp in python, R Language, power bi, Gnn AI and LLM is a plus

Background verification Mandatory PF Mandatory

.IN /

Data Scientist Python and Notebooks

Responsibilities

Job Description We are seeking a talented Data Scientist to join our team and drive datadriven decisionmaking across our organization The ideal candidate will have a strong background in statistical analysis machine learning and data visualization with experience working with large datasets in a Teradata environment

Responsibilities

Design and implement endtoend data science projects from problem definition to model deployment

Develop and apply advanced machine learning algorithms and statistical models to solve complex business problems

Collaborate with crossfunctional teams to identify opportunities for datadriven improvements

Conduct exploratory data analysis and feature engineering to prepare data for modeling

Create and maintain dashboards and reports to communicate insights to stakeholders

Optimize data collection procedures and ensure data quality

Stay current with the latest advancements in data science and machine learning techniques

Implement and maintain onpremise AIML solutions

Apply Explainable AI techniques to enhance model interpretability and transparency

Requirements

10-13 years of experience in data science or related field

Strong proficiency in Python R and SQL

Experience with Teradata and data lakelakehouse architectures

Expertise in machine learning algorithms statistical modeling and data visualization

Familiarity with big data technologies eg Hadoop Spark

Excellent problemsolving and communication skills

Experience with version control systems eg Git

Experience with onpremise AIML solutions

Knowledge of Explainable AI methods and their practical applications.

Location - Bengaluru,Hyderabad,Chennai,Pune

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Requirements

• Frontend Framework: Angular

• Servers : Tomcat, Jetty, JBoss, Nginx, Apache HTTP Server

• Tools : Maven, Log4j 2, JUnit 5, Mockito, Postman, Swagger,

JMeter, Logback

• OS : Windows, Linux

• Version Control : Git, GitHub

• IDE : Eclipse, STS, IntelliJ IDEA

• Messaging Systems : Apache Kafka

• Cloud : AWS, Azure

• DevOps Tools : Docker, Kubernetes, GitLab

• Frontend Framework: Angular

• Servers : Tomcat, Jetty, JBoss, Nginx, Apache HTTP Server

• Tools : Maven, Log4j 2, JUnit 5, Mockito, Postman, Swagger,

JMeter, Logback

• OS : Windows, Linux

• Version Control : Git, GitHub

• IDE : Eclipse, STS, IntelliJ IDEA

• Messaging Systems : Apache Kafka

• Cloud : AWS, Azure

• DevOps Tools : Docker, Kubernetes, GitLab

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Requirements

• Frontend Framework: Angular

• Servers : Tomcat, Jetty, JBoss, Nginx, Apache HTTP Server

• Tools : Maven, Log4j 2, JUnit 5, Mockito, Postman, Swagger,

JMeter, Logback

• OS : Windows, Linux

• Version Control : Git, GitHub

• IDE : Eclipse, STS, IntelliJ IDEA

• Messaging Systems : Apache Kafka

• Cloud : AWS, Azure

• DevOps Tools : Docker, Kubernetes, GitLab

• Frontend Framework: Angular

• Servers : Tomcat, Jetty, JBoss, Nginx, Apache HTTP Server

• Tools : Maven, Log4j 2, JUnit 5, Mockito, Postman, Swagger,

JMeter, Logback

• OS : Windows, Linux

• Version Control : Git, GitHub

• IDE : Eclipse, STS, IntelliJ IDEA

• Messaging Systems : Apache Kafka

• Cloud : AWS, Azure

• DevOps Tools : Docker, Kubernetes, GitLab

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Python, R, SQL,

predictive

modeling

Requirements

• Frontend Framework: Angular

• Servers : Tomcat, Jetty, JBoss, Nginx, Apache HTTP Server

• Tools : Maven, Log4j 2, JUnit 5, Mockito, Postman, Swagger,

JMeter, Logback

• OS : Windows, Linux

• Version Control : Git, GitHub

• IDE : Eclipse, STS, IntelliJ IDEA

• Messaging Systems : Apache Kafka

• Cloud : AWS, Azure

• DevOps Tools : Docker, Kubernetes, GitLab

• Frontend Framework: Angular

• Servers : Tomcat, Jetty, JBoss, Nginx, Apache HTTP Server

• Tools : Maven, Log4j 2, JUnit 5, Mockito, Postman, Swagger,

JMeter, Logback

• OS : Windows, Linux

• Version Control : Git, GitHub

• IDE : Eclipse, STS, IntelliJ IDEA

• Messaging Systems : Apache Kafka

• Cloud : AWS, Azure

• DevOps Tools : Docker, Kubernetes, GitLab

About AiDASH

AiDASH is making critical infrastructure industries climate-resilient and sustainable with satellites and AI. Using our full-stack SaaS solutions, customers in electric, gas, water utilities, transportation, and construction are transforming asset inspection and maintenance - and complying with biodiversity net gain mandates and carbon capture goals. AiDASH exists to safeguard critical infrastructure and secure the future of humanAIty. Learn more at

We are a Series C climate tech startup backed by leading investors, including Shell Ventures, National Grid Partners, G2 Venture Partners, Duke Energy, Edison International, Lightrock, Marubeni, among others. We have been recognized by Forbes two years in a row as one of "America's Best Startup Employers." We are also proud to be one of the few climate software companies in Time Magazine's "America's Top GreenTech Companies 2024". Deloitte Technology Fast 500 recently ranked us at No. 12 among San Francisco Bay Area companies, and No. 59 overall in their selection of the top 500 for 2024.

Join us in Securing Tomorrow

• • Extract, clean, and analyze large datasets from multiple sources using SQL and Python/R.
• Build and optimize data scraping pipelines to process large-scale unstructured data.
• Perform statistical analysis and data mining to identify trends, patterns, and anomalies.
• Develop automated workflows for data preparation and transformation.
• Conduct data quality checks and implement validation procedures.
• Build and validate ML models (classification, regression, clustering) using TensorFlow, Keras, and Pandas.
• Apply feature engineering to enhance accuracy and interpretability.
• Execute experiments, apply cross-validation, and benchmark model performance.
• Collaborate on A/B testing frameworks to validate hypotheses.
• Work on predictive analytics for wildfire risk detection and storm damage assessment.
• Translate complex business requirements into data science solutions.
• Develop predictive models and analytical tools that directly support CRIS decision-making.
• Create interactive dashboards and automated reports for stakeholders.
• Document methodologies and maintain clean, production-ready code repositories.

• • 4–5 years of hands-on experience in data science, analytics, or quantitative research.
• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or related field.
• Strong programming skills in Python for data analysis and machine learning.
• Proficiency in SQL and experience with relational databases.
• Experience with ML libraries (scikit-learn, pandas, NumPy, Keras, TensorFlow).
• Knowledge of statistical methods (clustering, regression, classification) and experimental design.
• Familiarity with data visualization tools (matplotlib, seaborn, ggplot2, Tableau, or similar).
• Exposure to cloud platforms (AWS, GCP, Azure) is a plus.
• Proven experience with end-to-end model development (from data exploration to deployment).
• Track record of delivering actionable insights that influenced business decisions.
• Strong analytical and problem-solving skills with attention to detail.

We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work.

We are committed to providing an inclusive and accessible interview experience for all candidates. Please let us know if you require any accommodation during the interview process, and we will make every effort to meet your needs.

About BrandIdea Analytics

At
BrandIdea Analytics
, we are redefining the way businesses understand markets by
delivering granular insights
from the building level upwards. Our analytics platform and frameworks empower some of India's

leading brands to make sharper, faster, and more effective decisions.We are looking for
Senior Data Scientists
who are passionate about solving complex business problems with data, scaling models to capture minute levels of granularity, and mentoring a next generation of analytics talent team.

Role Overview

As a Senior Data Scientist at BrandIdea, you will be part of the team that will drive the design and deployment of advanced analytics and AI/ML models that
bring precision to decision-making for leading brands like Coke, Cadbury's, Godrej Consumer Prdts, TAFE, Pepsi and many more.
You will collaborate closely with strategy, technology, and content teams, and will play a pivotal role in translating granular data into business impact.

Key Responsibilities

Analytics & Modeling

• Develop and scale
  predictive, prescriptive, and AI & ML models
  that handle granular datasets spanning the whole country. .
• Build robust forecasting, segmentation, and optimization models to solve sales, distribution, pricing, and consumer behavior challenges.

Data Strategy & Execution

• Leverage structured and unstructured datasets to create
  granular insights for clients in FMCG, Building Materials, BFSI, FMEG, and other industries
  .
• Work with large-scale distributed data systems and optimize model performance on
  real-world, high-volume, granular data.

Client Engagement & Business Impact

• Collaborate with client teams to identify problems, shape analytics solutions, and deliver insights that drive measurable business outcomes.
• Contribute thought leadership on how
  granular analytics
  can transform go-to-market strategies and brand growth.

Leadership & Mentoring

• Mentor junior data scientists and analysts on advanced methodologies and coding best practices.
• Contribute to BrandIdea's
  knowledge frameworks and IP creation
  in analytics.
• Excellent communication, presentation, and storytelling skills.

Qualifications

Education:

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, Data Science.

Experience:

• 6–10 years of professional experience in data science/advanced analytics.
• Proven track record of deploying models that delivered business impact at scale.
• Experience in consumer industries (FMCG, Building Materials, Consumer Durables, Retail, FMEG or similar sectors) is a plus.

Technical Skills:

• Strong coding expertise in
  Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch), SQL, and R
  .
• Deep understanding of
  predictive modeling, machine learning, NLP, time-series forecasting, and optimization methods
  .
• Hands-on experience with
  cloud platforms (AWS, GCP, or Azure)
  and production deployment.

What We Offer

• The opportunity to be the
  core of the Company -
  work on
  pioneering granular analytics frameworks
  that set global benchmarks.
• Exposure to diverse industries and categories.
• Competitive compensation and clear growth pathways.